COVID-19 and the judiciary: the case for access to testing Sudhi versus Union of India
Bibliographic record
Abstract
In an effort to protect citizens’ right-to-health, the Supreme Court of India on April 8th ordered the government to make COVID-19 testing free in all private hospitals and labs. The Court’s decision in Sudhi v. Union of India marked a significant step towards ensuring that all people, especially poor workers in the informal sector have access to necessary care. Five days later, however, after facing objections from private companies and the state, the Supreme Court reversed its previous order and made testing free for only those living below the poverty line, an obligation already mandated under the National Health Policy Scheme.This commentary suggests that judicial action should be strengthened, not hampered, in times of global health crisis. While no state has unlimited resources to ensure the protection of health, the judiciary should be emboldened to hold the state to account.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.034 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.044 | 0.045 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".